Fluorescence, temperature and narrow-band indices acquired from a UAV platform for water stress detection using a micro-hyperspectral imager and a thermal camera
The remote detection of water stress in a citrus orchard was investigated using leaf-level measurements of chlorophyll fluorescence and Photochemical Reflectance Index (PRI) data, seasonal time-series of crown temperature and PRI, and high-resolution airborne imagery. The work was conducted in an orchard where a regulated deficit irrigation (RDI) experiment generated a gradient in water stress levels. Stomatal conductance (Gs) and water potential (ο) were measured over the season on each treatment block. The airborne data consisted on thermal and hyperspectral imagery acquired at the time of maximum stress differences among treatments, prior to the re-watering phase, using a miniaturized thermal camera and a micro-hyperspectral imager on board an unmanned aerial vehicle (UAV). The hyperspectral imagery was acquired at 40cm resolution and 260 spectral bands in the 400-885nm spectral range at 6.4nm full width at half maximum (FWHM) spectral resolution and 1.85nm sampling interval, enabling the identification of pure crowns for extracting radiance and reflectance hyperspectral spectra from each tree. The FluorMOD model was used to investigate the retrieval of chlorophyll fluorescence by applying the Fraunhofer Line Depth (FLD) principle using three spectral bands (FLD3), which demonstrated that fluorescence retrieval was feasible with the configuration of the UAV micro-hyperspectral instrument flown over the orchard. Results demonstrated the link between seasonal PRI and crown temperature acquired from instrumented trees and field measurements of stomatal conductance and water potential. The sensitivity of PRI and Tc-Ta time-series to water stress levels demonstrated a time delay of PRI vs Tc-Ta during the recovery phase after re-watering started. At the time of the maximum stress difference among treatment blocks, the airborne imagery acquired from the UAV platform demonstrated that the crown temperature yielded the best coefficient of determination for Gs (r 2=0.78; p<0.05) and ο (r 2=0.34; p<0.001). Among the narrow-band indices calculated, the PRI 515 index (reference band=515nm) obtained better results than PRI 570, with r 2=0.59 (p<0.01) for Gs, and r 2=0.38 (p<0.001) for ο. The BGI1 index calculated from the blue (R 400) and green (R 550) bands resulted on the highest significance levels (p<0.001) for both Gs (r 2=0.62) and ο (r 2=0.49). Out of the structural indices assessed, RDVI, MTVI1 and TVI showed greater sensitivity for Gs (r 2=0.6; p<0.01) and ο (p<0.001) than NDVI. Chlorophyll fluorescence calculated from the micro-hyperspectral imagery with the FLD3 method tracked stress levels, obtaining r 2=0.67 (p<0.05) with stomatal conductance, and r 2=0.66 (p<0.001) with water potential. The work presented in this manuscript demonstrates the feasibility of thermal, narrow-band indices and fluorescence retrievals obtained from a micro-hyperspectral imager and a light-weight thermal camera on board small UAV platforms for stress detection in a heterogeneous tree canopy where very high resolution is required. © 2011 Elsevier Inc.
| Main Authors: | , , |
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| Format: | artículo biblioteca |
| Language: | English |
| Published: |
Elsevier
2012-02-15
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| Subjects: | Stress detection, Hyperspectral, Chlorophyll fluorescence, UAV, High resolution, Thermal, |
| Online Access: | http://hdl.handle.net/10261/87919 |
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